---
title: "CMT Data"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: scroll
    theme: cerulean
---

```{r setup, include=FALSE}
library(flexdashboard)
library(rio)
library(here)
library(tidyverse)
library(knitr)
library(kableExtra)
library(ggrepel)
library(colorblindr)
library(gt)
library(plotly)
library(reactable)

opts_chunk$set(echo = FALSE,
               fig.width = 6.5,
               fig.height = 8)

theme_set(theme_minimal(15))

```

# Month and Year Data 

Description of Data {.sidebar}
--------

This data has been collected from January 2018 to the present through collaboration of the Eugene Youth Concussion Management Team (CMT) 
```{r load-data, fig.width = 10, fig.height = 10, echo = FALSE, include=FALSE}
cmt <- import(here("data", "cmt_data.sav"),
               setclass = "tbl_df") %>% 
  characterize() %>% 
  janitor::clean_names() 

head(cmt)

cmt <- cmt %>% 
  rename(HEDCO = hedco_referral,
         PT = pt_referral,
         STRONG = psych_referral,
         CBIRT = cbirt_referral,
         Neurology = neuro_referral)


cmt$referral_month <- factor(cmt$referral_month, levels = c("January",
                                                            "February",
                                                            "March",
                                                            "April",
                                                            "May",
                                                            "June",
                                                            "July",
                                                            "August",
                                                            "September",
                                                            "October",
                                                            "November",
                                                            "December"))

cmt$referral_year <- factor(cmt$referral_year, levels = c("2018", "2019", "2020"))

```

Column {.tabset data-height=1000}
-----------------------------------------------------------------------

### Month Referrals Bar Graph 

```{r month plot 1}

plot_1 <- cmt %>% 
  count(referral_month, referral_year) %>% 
  ggplot(aes(referral_month, n)) +
  geom_col(aes(fill = referral_year), position = position_stack(reverse = TRUE)) +
  scale_fill_brewer(palette = "Dark2") +
  geom_text(aes(label = n), 
            position = position_stack(vjust = 0.5),
            color = "white",
            size = 5) +
  theme_minimal() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5)) +
  theme(axis.text.x = element_text(angle = 45),
        axis.text = element_text(size = 12),
        axis.title=element_text(size=12),
        legend.text = element_text(size = 12)) +
  labs(x = "Month",
       y = "Total",
       fill = "Referral \nYear",
       title = "Number of CMT Referrals by Month") 

ggplotly(plot_1)

```

### Month Referral Table
```{r month table}
cmt_descriptives_month <- cmt %>% 
  group_by(referral_month, sex) %>% 
  summarize(n=n())

knitr::kable(cmt_descriptives_month,
             caption = "Total Number of CMT Referrals by Month",
             col.names = c("Referral Month",
                           "Sex",
                           "Total")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))

```

### Month Referrals Line Plot
```{r month line plot}
cmt_count <- cmt %>% 
  count(referral_month)

ggplot(cmt_count, aes(referral_month, n, group = 1)) +
  geom_area(fill = "cornflowerblue",
            alpha = 0.3) +
  geom_line(lwd = 1.6, 
            color = "gray40") +
  geom_point(color = "blue",
             size = 3) +
  geom_smooth(color = "magenta",
              lwd = 1.4,
              se = FALSE) +
  geom_text_repel(aes(label = n, group = 1)) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5)) +
   theme(axis.text.x = element_text(angle = 45),
         axis.text = element_text(size = 12),
        axis.title=element_text(size=12)) +
  labs(x = "Referral Month",
       y = "Total",
       title = "CMT Referrals by Month")

```

Column {.tabset data-width=500}
-----------------------------------------------------------------------

### Year Referrals

```{r sex plot}

pd <- position_dodge(width = 1) 


cmt %>% 
 count(sex, referral_year) %>% 
 ggplot(aes(referral_year, n)) +
  geom_col(aes(fill = sex), position = pd) +
  scale_fill_OkabeIto() +
  geom_text(aes(label = n, group = sex), 
            position = pd,
            hjust = 2,
            size = 5,
            color = "white") +
  theme_minimal() +
  coord_flip() +
  scale_x_discrete(limits = rev(levels(cmt$referral_year))) +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 12),
        axis.title = element_text(size=12),
        legend.text = element_text(size = 12)) +
  guides(fill = guide_legend(reverse = TRUE)) +
  labs(x = "Referral Year",
       y = "Total",
       fill = "Sex",
       title = "Number of CMT Referrals per Year by Sex")


```

### Year Referral Table
```{r referral year table} 
cmt_descriptives_year <- cmt %>% 
  group_by(referral_year, sex) %>% 
  summarize(n=n())

knitr::kable(cmt_descriptives_year,
             caption = "Total Number of CMT Referrals by Year",
             col.names = c("Referral Year",
                           "Sex",
                           "Total")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>% 
  row_spec(1, color = "white", background = "#D7261E") %>% 
  row_spec(3, color = "white", background = "#D7261E") %>% 
  row_spec(5, color = "white", background = "#D7261E")

```


# School Referrals

Column {.tabset data-width=750}
-----------------------------------------------------------------------


### School Referral Plot
```{r school referral plot}
ggplot(cmt, aes(fct_rev(fct_infreq(school)))) +
  geom_bar(fill = "#56B4E9",
           color = "white",
           alpha = 0.9) +
   geom_text(aes(label = ..count..), stat = "count", 
            size = 4,
            nudge_y = -0.7,
            color = "white") +
  facet_wrap(~sex, ncol = 1) +
  coord_flip() + 
   theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
         axis.text = element_text(size = 12),
        axis.title=element_text(size=12)) +
   labs(x = "Referral School",
       y = "Total",
       title = "Number of CMT Referrals per School")

```

### School Referral Table
```{r school referral table}
cmt_descriptives_school <- cmt %>% 
  group_by(school) %>% 
  summarize(n=n())

knitr::kable(cmt_descriptives_school,
             caption = "Total Number of CMT Referrals per School",
             col.names = c("School",
                           "Total")) %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed"))

```


# CMT Referral Stats

### CMT Referral Status

```{r referral status plot}
cmt_discipline_referral <- cmt %>% 
  pivot_longer(cols = c("HEDCO",
                        "PT",
                        "STRONG",
                        "CBIRT",
                        "Neurology"),
               names_to = "referral",
               values_to = "status")



cmt_discipline_referral$status <- factor(cmt_discipline_referral$status, levels = c("Yes",
                                                                                    "No"))

plot_3_data <- cmt_discipline_referral %>% 
  count(referral, status)


plot_3 <- ggplot(plot_3_data, aes(referral, n)) +
  geom_col(aes(fill = status), position = position_dodge2(reverse = TRUE)) +
  scale_fill_OkabeIto() +
  theme_minimal() +
  coord_flip() +
  theme(plot.title = element_text(color = "black", size = 12, face = "bold", hjust = 0.5),
        axis.text = element_text(size = 12),
        axis.title = element_text(size=12),
        legend.text = element_text(size = 12)) +
  scale_x_discrete(expand = c(0,0)) +
  labs(x = "Referral Discipline",
       y = "Total",
       fill = "Sex",
       title = "Referral Status for Clients Entering CMT Tracking",
       fill = "Refferal \nStatus")

ggplotly(plot_3)

```